This constructor takes features as input, and you can either supply a single iVector input, estimated in batch-mode ('ivector'), or 'online' iVectors ('online_ivectors' and 'online_ivector_period', or none at all. More...

This constructor takes features as input, and you can either supply a single iVector input, estimated in batch-mode ('ivector'), or 'online' iVectors ('online_ivectors' and 'online_ivector_period', or none at all.

Note: it stores references to all arguments to the constructor, so don't delete them till this goes out of scope.

Parameters

[in]

opts

The options class. Warning: it includes an acoustic weight, whose default is 0.1; you may sometimes want to change this to 1.0.

[in]

nnet

The neural net that we're going to do the computation with

[in]

priors

Vector of priors– if supplied and nonempty, we subtract the log of these priors from the nnet output.

[in]

feats

The input feature matrix.

[in]

compiler

A pointer to the compiler object to use– this enables the user to maintain a common object in the calling code that will cache computations across decodes. Note: the compiler code has no locking mechanism (and it would be tricky to design one, as we'd need to lock the individual computations also), so the calling code has to make sure that if there are multiple threads, they do not share the same compiler object.

[in]

ivector

If you are using iVectors estimated in batch mode, a pointer to the iVector, else NULL.

[in]

online_ivectors

If you are using iVectors estimated 'online' a pointer to the iVectors, else NULL.

[in]

online_ivector_period

If you are using iVectors estimated 'online' (i.e. if online_ivectors != NULL) gives the periodicity (in frames) with which the iVectors are estimated.